• Journal of the Korean Institute of Landscape Architecture
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• v.24 no.4
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• pp.96-111
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• 1997

This study was carried out to identify users' choice behavior of theme parks. overland. Lotte World, Seoul Land, Dreamland and Children's Grand Park were selected as study areas. Both multinomial logic model(MNL), nested logic model(NMNL) and joint logit model wet$.$e test using a choice-based sample collected on study areas. Hausman-McFadden test showed that the MNL is not appropriate because the IIA assumption is violated. To avoid the problematic IIA assumption, the NMNL was tested. It splits similar alternatives into groups and nests separate decisions into hierarchical order to avoid the IIA assumption. Cluster analysis and discriminant analysis were conducted to find applicable nest structures. The inclusive value coefficient was 0.7788. It meant that sufficient condition of this model is met and users' choice behavior can be better understood by NMNL than MNL. The $\rho$2 value and accuracy of prediction of this model were 0.402 and 46.33% , respectively. Several comments were suggested to make the NMNL to be more reliable for future research on users' choice behavior of theme park.

• Journal of Korean Society of Rural Planning
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• v.24 no.4
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• pp.27-35
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• 2018

This study analyzed the factors influencing the choice of new farming type in order to prepare the countermeasures against structural changes of farm labor force. The analytical model was the multinomial logit model(MNL). The test for Independence and Irrelevance Alternatives(IIA) assumption in MNL shows that the IIA assumption in our data is rejected. Alternatively, we chose the multinomial probit model(MNP) that does not assume IIA. Data were obtained from 2010 census of Agriculture, Forestry and Fisheries of Statistics Korea. New farming types are succession(13.9%), return-to-farming(45.0%), part-time-farming(32.5%) and etc(8.6%). Analysis results showed that the characteristics of farms, commodity, management, and region influenced the choice of new farming type. This study is expected to help policy makers to produce support policies by new farming types in order to increase the number of new farmers and to make them easier to settle down in agriculture.

• Journal of Distribution Science
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• v.14 no.11
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• pp.61-73
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• 2016

Purpose - Marketing scholars have developed various types of mathematical models for describing marketing phenomenon, because there is no single model comprehensive enough to incorporate all the relevant marketing phenomena. This study tries to summarize the behavioral foundations and the mathematical derivations of the most widely used marketing models and discusses their strategic implications. This study selected four representative marketing models: multinomial logit(MNL) model, elimination-by-aspects(EBA) model, Hauser and Shugan model and Bass diffusion model. Especially, this study focuses on Hauser and Shugan(1983)'s Defender model and discusses the model's behavioral foundation and its implications. Research design, data, and methodology - Of the four selected model, the multinomial logit model is selected as the basic normative model and the other three models are described as descriptive models in contrast. Starting the discussion from the multinomial logit model, this study explains what important strategic variables are incorporated in each of the four models. The IIA(independence of irrelevant alternatives) axiom and Luce choice model is also discussed in relation to the multinomial logit model. The concept of 'efficient frontier' is discussed in relation to Hauser and Shugan's model. Graphs and tables are used to represent the key implications. No empirical study is included. Results - The analyses of the mathematical marketing models are shown to be very useful in understanding the essence of positioning strategy. The multinomial logit model implies the importance of increasing utility or consumer preference level. The EBA model implies the importance of lowering the inter-brand similarity and dominating the competitors. Hauser and Shugan model implies the importance of considering customer heterogeneity distribution in selecting the target market. Conclusions - It is shown that the concepts of 'efficient frontier' is useful in understanding the effectiveness of positioning strategy. Market positioning can be understood as occupying some place on the efficient frontier. The important strategic implications can be summarized as follows: Always try to increase customer preference by providing what they value, and differentiate from competing alternatives as much as possible. The best positioning strategy is to dominate all the competitors and the worst is to be dominated by the competitors.

• Safety and Health at Work
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• v.15 no.2
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• pp.200-207
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• 2024

Background: Workers are often exposed to hazardous heat due to their work environment, leading to various injuries. As a result of climate change, heat-related injuries (HRIs) are becoming more problematic. This study aims to identify critical contributing factors to the severity of occupational HRIs. Methods: This study analyzed historical injury reports from the Occupational Safety and Health Administration (OSHA). Contributing factors to the severity of HRIs were identified using text mining and model-free machine learning methods. The Multinomial Logit Model (MNL) was applied to explore the relationship between impact factors and the severity of HRIs. Results: The results indicated a higher risk of fatal HRIs among middle-aged, older, and male workers, particularly in the construction, service, manufacturing, and agriculture industries. In addition, a higher heat index, collapses, heart attacks, and fall accidents increased the severity of HRIs, while symptoms such as dehydration, dizziness, cramps, faintness, and vomiting reduced the likelihood of fatal HRIs. Conclusions: The severity of HRIs was significantly influenced by factors like workers' age, gender, industry type, heat index , symptoms, and secondary injuries. The findings underscore the need for tailored preventive strategies and training across different worker groups to mitigate HRIs risks.

• Journal of Korean Society of Transportation
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• v.25 no.1 s.94
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• pp.109-119
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• 2007

Increasingly, the emphasis in regional Passenger rail Planning is finding ways to more efficiently use existing facilities, with particular attention being Paid to Policies designed to spread Peak-Period travel demand more evenly throughout the week with consideration of train classification. In this context the individual's choice of time to travel is of crucial significance. This paper investigates the use of multinomial logit analysis to model ridership by rail classification using data collected for travel from Seoul to Busan during the one week in October 2004. The Particular model form that was successfully calibrated was the multinomial logit (MNL) model : it describes the choice mechanism that will Permit rail systems and operations to be planned on a more reliable basis. The assumption of independently and identically distributed(IID) error terms in the MNL model leads to its infamous independence from irrelevant alternatives (IIA) property. Relaxation of the IID assumption has been undertaken along a number or isolated dimensions leading to the development of the MNL model. For business and related rail travel patterns, the most important variables of choice were time and frequency to the chosen destination. The calibrated model showed high agreement between observed and Predicted market shares. The model is expected to be of use to railroad authorities in Planning and determining business strategies in the Increasingly competitive environment or regional rail transport.

• Environmental and Resource Economics Review
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• v.22 no.3
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• pp.521-545
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• 2013

This study applied choice experiment(CE) method(which is included in the stated preference method) to estimate values of some important attributes(i.e. type of estuary, water quality of river in estuary, water quality of sea in estuary, biodiversity level of estuary) of 4 major river(Hangang, Guemgang, Yeongsangang, Nakdonggang) estuaries in Korea. Although the multinomial logit model(MNL) is generally applied to analyse the CE data, testing for IIA assumption with the Hausman and McFadden test in MNL model shows that the IIA assumption in our data is rejected. Therefore, the heteroscedastic extreme value model(HEV) and the multinomial probit model(MNP) which are not based on the IIA assumption are used to analyse our CE data. As results, the coefficients and the elicited economic values of MNL model are seriously distorted if the IIA assumption is not satisfied in MNL model. The estimation results of MNP model show that the economic values are elicited as 352.3 billion won(95% C.I. 261.1 - 477.8 billion won) for natural estuary, 411.5 billion won(95% C.I. 338.5 - 525.5 billion won) for one grade improvement of river water quality in estuary, 358.9 billion won(95% C.I. 292.5 - 457.0 billion won) for one grade improvement of sea water quality in estuary, and 151.9 billion won(95% C.I. 99.0 - 218.6 billion won) for one grade improvement of biodiversity level of estuary. Therefore, the value of estuary is reached to 2,197.0 billion won(95% C.I. 1,721.0 - 2,879.9 billion won) if any natural estuary in 4 major rivers has good water quality of river in estuary(i.e. 2nd grade), good water quality of sea in estuary(i.e. 1st grade), and good biodiversity level of estuary.

• Asia Marketing Journal
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• v.1 no.1
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• pp.5.1-5.11
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• 1998

이 연구는 2차자료가 부족한 우리나라 슈퍼마켓 업체의 여건을 감안하여 간편하게 활용할 수 있는 입지분석 모델의 가능성을 탐구하였다. 연구모델은 두 가지 기준을 근거로 모두 네가지 모델을 설정하고 비교검토했다. 먼저 표본추출방법에 의해 내점객표본과 지역할당표본으로 분류하고, 이것을 다시 포함하는 변수의 범위에 따라 축소모델과 확장모델로 구분하였다. 공간상호작용모델의 추정에는 MNL(Multinomial Logit)방식을 이용했다. 분석결과 내점객표본으로 조사해서 얻은 응답자의 주거지와 주로 찾는 점포, 그리고 사전적으로 입수한 경쟁점포의 매장면적, 인접점포까지의 거리에 대한 자료만을 이용해서 추정한 가장 간단한 모델이 비교적 만족스러운 결과를 나타냈다.

• Journal of Korean Society of Transportation
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• v.22 no.6
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• pp.7-16
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• 2004

In mode choice decision, travelers consider not only travel time but also reliability of its modes. In this paper, reliability was expressed in terms of standard deviation and maximum delay that were measured based on triangular distribution. In order to estimate value of time and value of reliability, the Multinomial and Nested Logit models were used. The analysis results revealed that reliability is an important factor affecting mode choice decisions. Elasticity is used to estimate the impacts of the different policies and system improvements for water transportation mode. Among these policies, decision maker can assess and select the best alternative by doing the benefit and cost analysis based on a new market share, the value of time, and the value of reliability. Finally, a set of promising policies and system improvement of the water transportation were proposed.

• The Journal of the Korea Contents Association
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• v.12 no.6
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• pp.475-485
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• 2012

The purpose of this research study was to identify the factors that influence comsumer who make decisions on preferred coffee types. Data was collected for a month from September $12^{th}$ to October $10^{th}$, 2010 from 807 participants who visited a cafe' in Seoul. The Limdep(LIMited DEPendent) 8.0 program was used in analyzing the determinants for preferred types of coffee using the multinomial logit model(MNL) approach. The results revealed that there were four taste preference groups being Espresso, Americano, Cafe' Late, and Cafe' Mocha ; as well as confirming that demographic characteristics influenced the coffee selection attributes, type of packaging, preferred coffee brand, and visit frequencies. This study found seven coffee selection attributes were significant factors in influencing patrons choices for purchasing speciality coffee being age range, profession, packing status, elation, superficial appearance, weight control, and habitual, respectively. The research reflects the coffee selection attributes by the customers' preference and concludes that it would be helpful to make marketing strategy for particular coffee brands.

• Environmental and Resource Economics Review
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• v.32 no.3
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• pp.167-190
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• 2023

This study analyzes the potential demand for automobiles based on fuel type using survey data in Korea. The dependent variable of the model is the future desired fuel type, including gasoline, diesel, hybrid, electricity, and hydrogen. The main explanatory variables are the respondent demographic characteristics, key reasons for choosing vehicle fuel type and environmental awareness extracted via principal component analysis (PCA). Using a multinomial logit (MNL) model, we find that respondents who consider fuel economy and infrastructure increase the demand for a hybrid car but decrease the demand for electric and hydrogen vehicles. The denial-types increase the demand for gasoline (petrol) and diesel (light oil), and decrease the demand for electric vehicles. The anxiety-types increase the demand of hybrid vehicles, and decrease the demand for electric vehicles. In contrast, in the case of pro-types, the demand for diesel (light oil) hydrogen vehicles decreased.